A Proposal For Blind Fir Equalization Of Time-varying Channels

The multimodal and time-varying aspects of blind equalization problems in communication systems are treated here by means of an immune-inspired strategy capable of estimating the coefficients of the FIR equalization filter in an unsupervised manner. The associated optimization problem is solved by means of a population-based search technique characterized by a dynamic control of the population size and diversity maintenance. Static and time-varying channels have been proposed in simulated scenarios, aiming at indicating the tracking capability derived from the adaptive adjustment of the coefficients of the blind equalizer. © 2005 IEEE.914Arenas-Garcia, J., Gómes-Verdejo, V., Martínez-Ramon, M., Filgueiras-Vidal, A.R., Separate-variable adaptive combination of LMS adaptive filters for plant identification (2003) Proceedings of the IEEE XIII Workshop on Neural Network for Signal Processing, pp. 239-248. , ToulouseAttux, R.R.F., Loiola, M.B., Suyama, R., De Castro, L.N., Von Zuben, F.J., Romano, J.M.T., Blind search for optimal wiener equalizers using an artificial immune network model (2003) EURASIP Journal on Applied Signal Processing, 8, pp. 740-747Benveniste, A., Goursat, M., Blind equalizers (1984) IEEE Trans. on Communications, COM-32 (8), pp. 871-883De Castro, L.N., Timmis, J., (2002) Artificial Immune Systems: A New Computational Intelligence Approach, , Springer-VerlagDe Castro, L.N., Timmis, J., An artificial immune network for multimodal function optimization (2002) Proceedings of the IEEE Congress on Evolutionary Computation, 1, pp. 699-1674. , HawaiiDe França, F.O., Von Zuben, F.J., De Castro, L.N., An artificial immune network for multimodal function optimization on dynamic environments (2005) Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 1, pp. 289-296. , Washington D.C., JuneGaspar, A., Collard, P., From GAs to artificial immune systems: Improving adaptation in time dependent optimization (1999) Proceedings of the Congress on Evolutionary Computation (CEC), pp. 1859-1866. , Washington D.CHaykin, S., (1996) Adaptive Filter Theory. 3rd Ed., , Prentice HallHaykin, S., The blind deconvolution problem (1994) Blind Deconvolution, , Haykin, S. (ed.), Prentice-HallJohnson Jr., C.R., Anderson, B.O., Godard blind equalisation surface characteristics: White, zero-mean binary source case (1995) Int. Journal of Adaptive Control and Signal Processing, 9, pp. 301-324Suyama, R., Attux, R.R.F., Romano, J.M.T., Bellanger, M., Relations entre les critère du module constant et de Wiener (2003) Proc. of the GRETSI Symp. on Signal and Image Processing, , Sep., ParisWalker, J., Garrett, S., (2003) Dynamic Function Optimisation: Comparing the Performance of Clonal Selection and Evolutionary Strategies, pp. 273-284. , Lecture Notes in Computer Science 2787. Edinburg